Performance analysis of a Kalman Filter based attitude estimator for a Quad Rotor UAV

This paper analyzes the performance of an Extended Kalman Filter (EKF) based attitude estimator for a Quad Rotor Unmanned Aerial Vehicle (QRUAV). A non-linear dynamic model of the QRUAV, simulated in Matlab was complemented with an EKF based attitude estimator. The estimator fuses measurements obtained from simulated accelerometers and gyroscopes onboard the QRUAV. It is then shown that this estimator only results in adequate representation of the attitude when the translational velocity is large. This behavior is explained considering the dynamics of the vehicle and the onboard accelerometers. Also a possible method of exploiting this behavior for improving the estimation accuracy is suggested.